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Superposition of Functional Contours Based Prosodic Feature Extraction for Speech Processing

Shahid Ali Mahar1, Mumtaz Hussain Mahar1, Javed Ahmed Mahar1, Mehedi Masud2, Muneer Ahmad3, NZ Jhanjhi4,*, Mirza Abdur Razzaq1

1 Department of Computer Science, Shah Abdul Latif University, Khairpur, 66020, Sindh, Pakistan
2 Department of Computer Science, College of Computers and Information Technology, Taif University, P.O. Box 11099, Taif, 21944, Saudi Arabia
3 Department of Information Systems, Faculty of Computer Science & Information Technology, Universiti Malaya, Kuala Lumpur, 50603, Malaysia
4 School of Computer Science and Engineering, SCE, Taylor's University, Malaysia

* Corresponding Author: NZ Jhanjhi. Email: email

Intelligent Automation & Soft Computing 2021, 29(1), 183-197.


Speech signal analysis for the extraction of speech elements is viable in natural language applications. Rhythm, intonation, stress, and tone are the elements of prosody. These features are essential in emotional speech, speech to speech, speech recognition, and other applications. The current study attempts to extract the pitch and duration from historical Sindhi sound clips using the functional contours model’s superposition. The sampled sound clips contained the speech of 273 undergraduates living in 5 districts of the Sindhi province. Several Python libraries are available for the application of this model. We used these libraries for the extraction of prosodic data from a variety of sound units. The spoken sentences were categorically segmented into words, syllables, and phonemes. A speech analyzer investigated the acoustics of sounds with the power spectral density method. Meanwhile, a speech database was divided into parts contains words of different sizes (ranging from 1-letter to 5-letter words). The results illustrated the production of both minimum and maximum μ sound durations and pitches from the inhabitants of Khairpur and Ghotki districts, respectively. Both districts lie in the upper part of the Sindh province. In addition, the second parameter approach, observed versus obtained, was used to compare outcomes. We observed 5250 and 4850 durations and pitches, respectively.


Cite This Article

APA Style
Mahar, S.A., Mahar, M.H., Mahar, J.A., Masud, M., Ahmad, M. et al. (2021). Superposition of functional contours based prosodic feature extraction for speech processing. Intelligent Automation & Soft Computing, 29(1), 183-197.
Vancouver Style
Mahar SA, Mahar MH, Mahar JA, Masud M, Ahmad M, Jhanjhi N, et al. Superposition of functional contours based prosodic feature extraction for speech processing. Intell Automat Soft Comput . 2021;29(1):183-197
IEEE Style
S.A. Mahar et al., "Superposition of Functional Contours Based Prosodic Feature Extraction for Speech Processing," Intell. Automat. Soft Comput. , vol. 29, no. 1, pp. 183-197. 2021.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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